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Updated: Apr 24, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Integrating Artificial Intelligence Into Health Informatics and Information Education: A Competency-Based Framework

Shannon H Houser¹, Cathy A Flite², Susan L Foster³

¹Health Services Administration, University of Alabama at Birmingham.

Advances in Health Information Science and Practice

|April 23, 2026

Summary

This summary is machine-generated.

Artificial intelligence (AI) integration in health informatics and information management (HIIM) education requires a structured approach. A new competency-based framework guides students from basic knowledge to real-world AI application, ensuring ethical and effective use.

Keywords:

AI-enhanced learning Miller’s Pyramid artificial intelligence competency-based learning educational frameworks health informatics and information education responsible AI in education

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Last Updated: Apr 24, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Area of Science:

Health Informatics
Educational Technology
Artificial Intelligence

Background:

The increasing adoption of AI in healthcare necessitates AI literacy in Health Informatics and Information Management (HIIM) professionals.
Current HIIM curricula require updates to address the ethical complexities and practical applications of AI tools.
Preparing the future healthcare workforce for AI integration is crucial for effective and responsible technology adoption.

Purpose of the Study:

To propose a competency-based framework for integrating Artificial Intelligence (AI) into Health Informatics and Information Management (HIIM) curricula.
To utilize Miller's Pyramid of Clinical Competence for scaffolding progressive AI learning outcomes.
To foster problem-solving abilities and workforce readiness in AI-driven healthcare environments.

Main Methods:

Development of a competency-based framework using Miller's Pyramid for progressive learning.
Integration of AI concepts across foundational knowledge, applied reasoning, simulation, and real-world performance.
Embedding ethical considerations throughout the AI learning process.
Alignment of AI-enhanced assignments with core HIIM domains.

Main Results:

The proposed framework facilitates a structured progression of AI competencies for HIIM students.
Educators can guide students from understanding AI to performing with AI tools in simulated and real-world settings.
The framework supports the development of technical proficiency, ethical awareness, and professional confidence.

Conclusions:

A competency-based framework effectively integrates AI into HIIM education, addressing both technical skills and ethical considerations.
This model prepares students for the AI-driven healthcare landscape, enhancing problem-solving and workforce readiness.
The framework offers flexible guidance for diverse educational settings to cultivate AI-proficient and ethically-minded health informaticians.